Optimal Uni ed Approach to Warping and Overlapped BlockMotion Estimation in Video

Among the class of block-based motion estimators, warping prediction and overlapped block motion estimation have emerged recently as two of the most eeective inter-frame estimation algorithms. Warping estimation is based on linear operations in the motion eld, while overlapped block estimators are based on a linear sum of motion-based estimators in the intensity eld. In this paper, we propose a uniied framework for estimation of pixel intensities based jointly on warping and overlapped blocks. We motivate our estimator through a discussion of ambiguities in an incomplete (sparsely sampled) motion eld; and that diierent object motions call for resolution of motion ambiguities in either the motion or intensity domain. We ooer a means of optimizing the joint estimator simultaneously in intensity and motion domains, thus guaranteeing improved performance compared to warping and overlapped block estimators, which the joint model contains as special cases. Furthermore, the joint framework provides an excellent vehicle for studying the interactions and relative merits of warping and overlapped block estimators in the presense of various motion scenarios.